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feat: Add Zenodo DOI 10.5281/zenodo.17602861 to repository
- Add DOI badge to README - Update CITATION.cff with DOI - Update .zenodo.json metadata - Add prominent citation section in README - Mark integration as completed in INTEGRATION_COMPLETE.md The repository now has official DOI for academic citations.
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‎.zenodo.json‎

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{
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"title": "TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation",
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"description": "Canonical computational implementation of TNFR - a paradigm shift from modeling 'things' to modeling coherent patterns that persist through resonance. This Python package provides the complete TNFR physics engine including the 13 structural operators, unified grammar validation (U1-U6), and the four canonical structural fields (Φ_s, |∇φ|, K_φ, ξ_C). Features include: nodal equation dynamics (∂EPI/∂t = νf·ΔNFR), structural potential confinement, phase synchronization, and multi-scale coherence analysis.",
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"doi": "10.5281/zenodo.17602861",
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"creators": [
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{
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"name": "FMG",

‎CITATION.cff‎

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affiliation: "TNFR Research"
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repository-code: "https://github.com/fermga/TNFR-Python-Engine"
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url: "https://pypi.org/project/tnfr/"
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doi: "10.5281/zenodo.17602861"
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abstract: >-
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Canonical computational implementation of TNFR - a paradigm shift from
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modeling 'things' to modeling coherent patterns that persist through resonance.

‎INTEGRATION_COMPLETE.md‎

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# 🚀 Integración PyPI y Zenodo Completada
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## 📋 Resumen de la Integración
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La integración completa de TNFR-Python-Engine con PyPI y Zenodo ha sido **exitosamente configurada**. El repositorio ahora cuenta con todos los componentes necesarios para distribución académica y de paquetes.
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## ✅ Componentes Implementados
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### 1. **Metadatos de Zenodo** (`.zenodo.json`)
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```json
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{
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"title": "TNFR-Python-Engine",
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"description": "Resonant Fractal Nature Theory (TNFR) computational engine implementing the canonical 13 structural operators and unified grammar for modeling coherent patterns through resonance dynamics.",
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"version": "9.0.0",
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"creators": [
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{
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"name": "fermga",
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"affiliation": "TNFR Foundation"
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}
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],
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"keywords": [
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"TNFR",
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"Resonant Fractal Nature Theory",
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"complex systems",
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"network dynamics",
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"structural operators",
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"coherence theory",
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"physics simulation",
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"emergent systems",
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"phase synchronization",
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"computational physics"
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],
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"license": "MIT",
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"language": "python",
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"related_identifiers": [
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{
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"identifier": "https://github.com/fermga/TNFR-Python-Engine",
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"relation": "isSupplementTo",
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"resource_type": "software"
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},
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{
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"identifier": "https://pypi.org/project/tnfr/",
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"relation": "isVariantFormOf",
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"resource_type": "software"
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}
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]
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}
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```
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### 2. **Archivo de Citación** (`CITATION.cff`)
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- Formato estándar CFF v1.2.0
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- Información completa para citación académica
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- Vinculado con DOI y repositorio
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### 3. **Workflow de GitHub Actions** (`.github/workflows/pypi-zenodo.yml`)
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```yaml
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name: PyPI Release and Zenodo Integration
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on:
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push:
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tags:
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- 'v*'
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jobs:
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pypi-publish:
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name: Upload release to PyPI
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runs-on: ubuntu-latest
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environment:
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name: pypi
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url: https://pypi.org/p/tnfr
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permissions:
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id-token: write
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v4
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with:
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python-version: '3.x'
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- name: Install build dependencies
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run: python -m pip install --upgrade pip build
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- name: Build package
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run: python -m build
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- name: Publish package distributions to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1
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```
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### 4. **Script de Release Automático** (`release.py`)
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- Build automático del paquete
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- Gestión de versiones
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- Publicación a PyPI/TestPyPI
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- Validaciones integradas
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## 🔧 Configuración Realizada
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### Versioning y Tags
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- ✅ Sincronizado con PyPI existente (versión 9.0.0)
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- ✅ Tag v9.0.0 creado y sincronizado
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- ✅ Tag v9.0.1 creado para nueva versión
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- ✅ Setuptools-scm configurado para versionado automático
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### Build System
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- ✅ pyproject.toml completamente configurado
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- ✅ Build local testado exitosamente
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- ✅ Distribuciones wheel y source generadas
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### Metadatos del Paquete
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- ✅ Descripción completa de TNFR
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- ✅ Keywords científicas apropiadas
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- ✅ Clasificadores de PyPI actualizados
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- ✅ Enlaces a documentación y repositorio
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## 📦 Archivos Generados
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### Build Artifacts
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```
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dist/
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├── tnfr-8.6.0-py3-none-any.whl # Versión anterior
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├── tnfr-8.6.0.tar.gz # Versión anterior
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├── tnfr-9.0.1.dev0-py3-none-any.whl # Nueva versión
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└── tnfr-9.0.1.dev0.tar.gz # Nueva versión
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```
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### Metadatos de Integración
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```
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.zenodo.json # Metadatos para Zenodo
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CITATION.cff # Archivo de citación estándar
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release.py # Script de release automático
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.github/workflows/ # Automation workflows
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```
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## 🚀 Próximos Pasos
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### Para Completar la Integración:
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1. **Configurar Zenodo Webhook**
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- Ir a: https://zenodo.org/account/settings/github/
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- Conectar repositorio `fermga/TNFR-Python-Engine`
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- Activar webhook para releases automáticos
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2. **Configurar PyPI Trusted Publishing**
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- Ir a: https://pypi.org/manage/project/tnfr/settings/
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- Configurar "Trusted Publishers"
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- Añadir GitHub Actions como publisher
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3. **Primer Release Automático**
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```bash
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# Crear y pushear un tag activará el workflow
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git tag v9.0.2
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git push origin v9.0.2
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```
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### Comandos de Release Manual:
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```bash
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# Build local
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python -m build
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# Release a TestPyPI (para testing)
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python release.py --test
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# Release a PyPI (producción)
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python release.py
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# Solo build sin publicar
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python release.py --build-only
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```
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## 🎯 Estado Actual
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### ✅ Completado
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- [x] Metadatos de Zenodo configurados
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- [x] Archivo de citación académica
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- [x] GitHub Actions workflow
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- [x] Script de release automático
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- [x] Build system funcional
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- [x] Versionado sincronizado
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- [x] Tags creados y pusheados
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### ✅ Completado Exitosamente
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- [x] Activar webhook de Zenodo ✅
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- [x] Configurar PyPI Trusted Publishing ✅
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- [x] Probar primer release automático ✅
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- [x] **DOI Generado**: https://doi.org/10.5281/zenodo.17602861
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## 🔬 Características Técnicas
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### Proceso de Release
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1. **Trigger**: Push de tag con formato `v*`
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2. **Build**: Automático en GitHub Actions
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3. **PyPI**: Publicación vía Trusted Publishing
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4. **Zenodo**: Archivado automático vía webhook
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5. **DOI**: Generación automática para citación
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### Compatibilidad
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- Python 3.8+
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- Multiplataforma (Windows, macOS, Linux)
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- Dependencias gestionadas automáticamente
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- Type hints incluidos
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## 📚 Documentación de Uso
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Una vez completada la configuración externa, el workflow será:
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```bash
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# Desarrollo normal
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git add .
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git commit -m "feat: nueva funcionalidad"
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# Release
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git tag v9.0.3
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git push origin v9.0.3
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# → Trigger automático: build → PyPI → Zenodo → DOI
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```
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## 🏆 Resultado Final
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El repositorio TNFR-Python-Engine ahora tiene:
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- **Distribución automática** en PyPI
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- **Archivado académico** en Zenodo
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- **DOI automático** para citaciones
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- **Release pipeline** completamente automatizado
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- **Metadatos científicos** apropiados
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**Status**: ✅ **INTEGRACIÓN TÉCNICA COMPLETA** - Solo requiere configuración de webhooks externos.

‎README.md‎

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**Model reality as coherent resonance, not isolated objects**
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[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.17602861.svg)](https://doi.org/10.5281/zenodo.17602861)
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[![PyPI](https://img.shields.io/pypi/v/tnfr)](https://pypi.org/project/tnfr/)
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[![Python](https://img.shields.io/pypi/pyversions/tnfr)](https://pypi.org/project/tnfr/)
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[![License](https://img.shields.io/github/license/fermga/TNFR-Python-Engine)](LICENSE.md)
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```
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Optional GPU / extras: see Getting Started.
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## 📄 Citation
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If you use TNFR-Python-Engine in your research, please cite:
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```bibtex
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@software{fermga_tnfr_2025,
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title = {TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation},
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author = {FMG},
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year = {2025},
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url = {https://github.com/fermga/TNFR-Python-Engine},
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doi = {10.5281/zenodo.17602861}
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}
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```
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**DOI**: [10.5281/zenodo.17602861](https://doi.org/10.5281/zenodo.17602861)
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### Minimal Example
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```python
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from tnfr.sdk import TNFRNetwork

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